Game Theory Based Interactively Decision Making Between Electric Vehicles And Smart Grids

Coordinated electric vehicle(EV)charging is an important method to accelerate the electrification of energy supply in transportation systems.In the traditional coordinated EV charging methods,the main purposes are to meet the energy requirements of EVs or to benefit the power systems.These methods can not be adopted directly when EVs and smart grids make decisions interactively.Under this emerging scenario,game theory is employed to provide high quality charging services for EVs,and stimulate EVs to cooperative with smart grids,e.g.demand response and reserve provision.The main works of this dissertation are summarized as follows.To clarify the duties of EVs in smart grids,the trend of EVs is summarized and forecasted from the prespective of transportation systems and smart grids,respectively.The analysis methodology of game theory is summarized accordingly.The application of game theory in coordinated EV charging is reviewed from the view of non-aggregation game and aggregation game,respectively.The application status of game theory in interactively decision making between EVs and smart grids are illuminated as well.For the energy coordination between EVs and smart grids,when EVs are not aggregated,a generalized Nash game(GNG)based method is proposed.In this method,the Quality of service(QoS)of EV charging is defined based on the network calculus theory.In GNG,the charging plan of each EV is optimized to minimize its charging cost,while considering the total charging power limitation for all EVs.The existence and uniqueness of generalized Nash equilibrium are proved based on quasi variational inequality theory(QVI).To realize the jointed energy and reserve coordination among EVs and smart grids,a generalized Stackelberg game(GSG)based decision making technique is proposed.In GSG,EVs are followers aiming to maximize their benefits through optimizing the charging and reserve plans,while responding to the energy and reserve prices,which are settled by the smart grid.The smart gird is the leader to realize the energy and reserve coordination with EVs,through optimizing the energy and reserve prices for each EV.The existence and uniqueness of generalized Stackelberg equilibrium(GSE)are proved based on QVI.To compute the GSE,this GSG is reformulated to an optimization problem.To realize the coordination of EV charging stations(EVCSs)with the active distribution network(ADN),which EVCSs are integrated to,a supply function equilibrium(SFE)based method is proposed.In the SFE,EVCS s act as the leaders to maximize their benefits,by optimizing their demand curves to affect the distribution local marginal prices.The ADN is the common follower,who aims to maximize the social welfare by optimizing the charging plans of EVCSs.The SFE is reformulated to a mathematical programming with equilibrium constraints(MPEC).The existence of equilibriums in SFE is demonstrated accordingly.To realize the jointed energy and reserve sharing among EVCSs and ADN,who can participate into the jointed energy and reserve market,a cooperative game based mechanism is proposed.In this cooperative game,a jointed energy and reserve decision making technique is proposed for each EVCS,where the Qo S constraints are modelled based on network calculus theory.Furthermore,an uncertain dispatch model is proposed for the ADN.This dispatch method is reformulated to its deterministic robustness counterpart,based on affine robust optimization.A convex game for the cooperation of EVCSs and ADN is put forward based on the characteristics function related to the utility functions of EVCSs and ADN.The stability of the coalition is shown and the surplus distribution method based on Shapely value is given as well.